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Xiao Sun 0013
Person information
- affiliation: Meta Platforms, Inc., Menlo Park, CA, USA
- affiliation: IBM T. J. Watson Research Center, Yorktown Heights, NY, USA
- affiliation (PhD 2013): Yale University, New Haven, CT, USA
Other persons with the same name
- Xiao Sun — disambiguation page
- Xiao Sun 0001 — Shanghai Artificial Intelligence Laboratory, China (and 1 more)
- Xiao Sun 0002 — Motorola (and 1 more)
- Xiao Sun 0003
— Hefei University of Technology, School of Computer and Information, China (and 2 more)
- Xiao Sun 0004 — Stony Brook University, Stony Brook , NY, USA
- Xiao Sun 0005
- Xiao Sun 0006
- Xiao Sun 0007
- Xiao Sun 0008
- Xiao Sun 0009
- Xiao Sun 0010 — Pennsylvania State University, University Park, PA, USA
- Xiao Sun 0011 — Peking University, Beijing, China
- Xiao Sun 0012
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2020 – today
- 2023
- [c10]Jiaqi Zhai
Revisiting Neural Retrieval on Accelerators. KDD 2023: 5520-5531 - [i3]Jiaqi Zhai, Zhaojie Gong, Yueming Wang, Xiao Sun, Zheng Yan
Revisiting Neural Retrieval on Accelerators. CoRR abs/2306.04039 (2023) - 2022
- [j2]Sae Kyu Lee
A 7-nm Four-Core Mixed-Precision AI Chip With 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling. IEEE J. Solid State Circuits 57(1): 182-197 (2022) - 2021
- [c9]Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun
4-Bit Quantization of LSTM-Based Speech Recognition Models. Interspeech 2021: 2586-2590 - [c8]Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Wang, Sanchari Sen, Jintao Zhang, Ankur Agrawal, Monodeep Kar, Shubham Jain, Alberto Mannari, Hoang Tran, Yulong Li, Eri Ogawa, Kazuaki Ishizaki, Hiroshi Inoue, Marcel Schaal, Mauricio J. Serrano, Jungwook Choi, Xiao Sun
RaPiD: AI Accelerator for Ultra-low Precision Training and Inference. ISCA 2021: 153-166 - [c7]Ankur Agrawal, Sae Kyu Lee, Joel Silberman, Matthew M. Ziegler, Mingu Kang, Swagath Venkataramani, Nianzheng Cao, Bruce M. Fleischer, Michael Guillorn, Matt Cohen, Silvia M. Mueller, Jinwook Oh, Martin Lutz, Jinwook Jung, Siyu Koswatta, Ching Zhou, Vidhi Zalani, James Bonanno, Robert Casatuta, Chia-Yu Chen, Jungwook Choi, Howard Haynie, Alyssa Herbert, Radhika Jain, Monodeep Kar, Kyu-Hyoun Kim
A 7nm 4-Core AI Chip with 25.6TFLOPS Hybrid FP8 Training, 102.4TOPS INT4 Inference and Workload-Aware Throttling. ISSCC 2021: 144-146 - [i2]Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan:
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. CoRR abs/2104.11125 (2021) - [i1]Andrea Fasoli, Chia-Yu Chen, Mauricio J. Serrano, Xiao Sun, Naigang Wang, Swagath Venkataramani, George Saon, Xiaodong Cui, Brian Kingsbury, Wei Zhang, Zoltán Tüske, Kailash Gopalakrishnan:
4-bit Quantization of LSTM-based Speech Recognition Models. CoRR abs/2108.12074 (2021) - 2020
- [j1]Swagath Venkataramani
Efficient AI System Design With Cross-Layer Approximate Computing. Proc. IEEE 108(12): 2232-2250 (2020) - [c6]Chia-Yu Chen, Jiamin Ni, Songtao Lu, Xiaodong Cui, Pin-Yu Chen, Xiao Sun, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Wei Zhang, Kailash Gopalakrishnan:
ScaleCom: Scalable Sparsified Gradient Compression for Communication-Efficient Distributed Training. NeurIPS 2020 - [c5]Xiao Sun, Naigang Wang, Chia-Yu Chen, Jiamin Ni, Ankur Agrawal, Xiaodong Cui, Swagath Venkataramani, Kaoutar El Maghraoui, Vijayalakshmi Srinivasan, Kailash Gopalakrishnan:
Ultra-Low Precision 4-bit Training of Deep Neural Networks. NeurIPS 2020 - [c4]Jinwook Oh, Sae Kyu Lee, Mingu Kang, Matthew M. Ziegler, Joel Silberman, Ankur Agrawal, Swagath Venkataramani, Bruce M. Fleischer, Michael Guillorn, Jungwook Choi, Wei Wang, Silvia M. Mueller, Shimon Ben-Yehuda, James Bonanno, Nianzheng Cao, Robert Casatuta, Chia-Yu Chen, Matt Cohen, Ophir Erez, Thomas W. Fox, George Gristede, Howard Haynie, Vicktoria Ivanov, Siyu Koswatta, Shih-Hsien Lo, Martin Lutz, Gary W. Maier, Alex Mesh, Yevgeny Nustov, Scot Rider, Marcel Schaal, Michael Scheuermann, Xiao Sun
A 3.0 TFLOPS 0.62V Scalable Processor Core for High Compute Utilization AI Training and Inference. VLSI Circuits 2020: 1-2
2010 – 2019
- 2019
- [c3]Ankur Agrawal, Bruce M. Fleischer, Silvia M. Mueller, Xiao Sun
DLFloat: A 16-b Floating Point Format Designed for Deep Learning Training and Inference. ARITH 2019: 92-95 - [c2]Xiao Sun, Jungwook Choi, Chia-Yu Chen, Naigang Wang, Swagath Venkataramani, Vijayalakshmi Srinivasan, Xiaodong Cui, Wei Zhang, Kailash Gopalakrishnan:
Hybrid 8-bit Floating Point (HFP8) Training and Inference for Deep Neural Networks. NeurIPS 2019: 4901-4910 - 2016
- [c1]Ismail Bayram, Enes Eken, Xue Wang, Xiao Sun
Adaptive refreshing and read voltage control scheme for FeDRAM. ISCAS 2016: 1154-1157
Coauthor Index
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last updated on 2024-12-13 19:12 CET by the dblp team
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